Large-scale parameterization of 3D building morphology in complex urban landscapes using aerial LiDAR and city administrative data

The form and function of the modern city are defined by the three-dimensional contours of the built environment. The morphology of the urban landscape has significant implications for a city's sustainability, efficiency, and resilience. With advancements in remote sensing, especially airborne Light Detection and Ranging (LiDAR), the potential exists to model urban topography at an unprecedented spatial resolution and granularity and extract previously unavailable characteristics of individual buildings. In this study, we demonstrate the application of point-based voxelization techniques to extract design parameters in complex urban environments at unprecedented scale using New York City, and its more than 1,000,000 buildings, as a test case. Covering approximately 800 km², we develop a 1 m² resolution Digital Surface Model (DSM) derived from aerial LiDAR point cloud data, together with city administrative records, to calculate building massing, height, volume, exposed surface area, and compactness ratios for every building in the City. The proposed scalable approach creates a significant opportunity for city administrators, urban planners, architectural engineers, and building designers to understand the relationship between urban morphology and a range of infrastructure and environmental systems.